ASCQ-Me measures were evaluated using both
classical and modern psychometric theory:

Both exploratory and confirmatory factor
analysis were used to examine the unidimensionality assumption for each of the
five ASCQ-Me domains (Emotional Impact, Pain Impact, Sleep Impact, Social
Functioning Impact, and Stiffness Impact). Results of these analyses supported the unidimensionality of each item bank.

After the IRT assumptions had been
evaluated and confirmed, we fitted the unidimensional Graded Response Model
(Samejima, 1969) to the data to create individual scores based on item
calibrations. Because some items might not be equally valid across different
types of respondents leading to bias in measurement, a differential item
function (DIF) analysis was conducted for each of the six measures in ASCQ-Me
and items showing DIF were removed from the item banks.

After the full item banks of all five
ASCQ-Me measures were defined and all the items had been calibrated, five items
were selected from each item bank to create a short form; this would enable
users to minimize respondent burden even if they did not have access to the
CATs. Items were chosen to represent the content of the item bank and to
represent different levels of severity for each of the five health dimensions.

To examine the discriminate validity,
participants were divided into three groups according to their SCD severity
scores, representing low, medium, and high level of severity, respectively.
Since there were 9 possible severity scores (i.e., 0 to 8), the percentile
corresponding to each level of severity in the entire sample was calculated,
and severity scores closest to the 33rd and 66th
percentile were regarded as the cut-off values to determine the three severity
groups.